AI Infrastructure Engineer
San Jose, CA - USA
Job Summary
Job Title: AI Infrastructure Engineer (Nutanix AI Platform)
Location: San Jose CA (Hybrid/Onsite Preferred) Duration: 12 months Contract Experience: 10 YearsRate: Negotiable Position Overview
We are seeking a highly experienced AI Infrastructure Engineer to architect deploy and optimize enterprise-scale AI infrastructure solutions leveraging the Nutanix ecosystem. The ideal candidate will have deep expertise in Nutanix Cloud Infrastructure (NCI) AOS/AHV Nutanix Kubernetes Platform (NKP) GPU-accelerated computing and hybrid cloud environments.
This role focuses on building scalable high-performance infrastructure that supports Large Language Models (LLMs) Generative AI workloads AI training and AI inference platforms across on-premises and cloud environments.
The selected candidate will serve as a Subject Matter Expert (SME) for Nutanix AI infrastructure and will work closely with architecture cloud platform networking and security teams.
Required Skills (Must Have) Nutanix Platform Expertise-
Strong hands-on experience with:
-
Nutanix Cloud Infrastructure (NCI)
-
Nutanix AOS (Acropolis Operating System)
-
Nutanix AHV (Acropolis Hypervisor)
-
Nutanix Cloud Manager (NCM)
-
Nutanix Flow
-
Nutanix Objects and Files
-
-
Extensive experience with:
-
Nutanix Kubernetes Platform (NKP)
-
Kubernetes cluster deployment and administration
-
Container orchestration and workload management
-
AI/ML workload deployment in Kubernetes environments
-
-
Experience designing and managing GPU-enabled environments
-
Hands-on experience with:
-
NVIDIA GPU ecosystem (A100 H100 CUDA GPU Passthrough vGPU)
-
AMD GPU ecosystem
-
-
Experience supporting AI model training and inference workloads
-
Terraform
-
Infrastructure as Code (IaC)
-
Nutanix Calm
-
Automated provisioning and lifecycle management
-
Prometheus
-
Grafana
-
ELK Stack
-
OpenTelemetry
-
Monitoring logging alerting and performance tuning
-
Design and implement scalable AI infrastructure platforms using Nutanix technologies.
-
Build optimized environments supporting Generative AI LLM training and inference workloads.
-
Design high-performance compute storage and networking architectures for AI applications.
-
Architect hybrid cloud solutions leveraging Nutanix Cloud Clusters (NC2).
-
Enable seamless workload portability between on-premises environments and public cloud platforms.
-
Support cloud bursting and dynamic workload scaling.
-
Deploy manage and optimize AI workloads on Nutanix Kubernetes Platform (NKP).
-
Design highly available and resilient containerized environments.
-
Implement workload automation and orchestration best practices.
-
Design high-performance storage solutions using Nutanix Objects and Nutanix Files.
-
Optimize storage architectures for AI/ML datasets and model repositories.
-
Ensure data availability scalability and performance.
-
Implement Zero-Trust security principles.
-
Utilize Nutanix Flow for micro-segmentation and workload security.
-
Collaborate with security and networking teams to protect sensitive AI data.
-
Optimize GPU utilization and AI infrastructure performance.
-
Configure GPU Passthrough and vGPU environments.
-
Improve resource efficiency scalability and operational costs.
-
Establish enterprise monitoring logging and alerting frameworks.
-
Ensure high availability disaster recovery and fault tolerance.
-
Perform root cause analysis and capacity planning.
-
Experience supporting AI/ML platforms LLMs and Generative AI initiatives.
-
Experience with AI model serving frameworks and inference platforms.
-
Knowledge of MLOps AI platform engineering and data pipelines.
-
Experience working in enterprise-scale hybrid cloud environments.
-
Nutanix certifications highly preferred.
-
10 years of Infrastructure Cloud Platform Engineering or Architecture experience.
-
Strong enterprise-level Nutanix experience.
-
Experience supporting Kubernetes-based production environments.
-
Experience with GPU-enabled infrastructure and AI workloads.